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ConQuer: efficient management of inconsistent databases

Published: 14 June 2005 Publication History

Abstract

Although integrity constraints have long been used to maintain data consistency, there are situations in which they may not be enforced or satisfied. In this paper, we present ConQuer, a system for efficient and scalable answering of SQL queries on databases that may violate a set of constraints. ConQuer permits users to postulate a set of key constraints together with their queries. The system rewrites the queries to retrieve all (and only) data that is consistent with respect to the constraints. The rewriting is into SQL, so the rewritten queries can be efficiently optimized and executed by commercial database systems.We study the overhead of resolving inconsistencies dynamically (at query time). In particular, we present a set of performance experiments that compare the efficiency of the rewriting strategies used by ConQuer. The experiments use queries taken from the TPC-H workload. We show that the overhead is not onerous, and the consistent query answers can often be computed within twice the time required to obtain the answers to the original (non-rewritten) query.

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cover image ACM Conferences
SIGMOD '05: Proceedings of the 2005 ACM SIGMOD international conference on Management of data
June 2005
990 pages
ISBN:1595930604
DOI:10.1145/1066157
  • Conference Chair:
  • Fatma Ozcan
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Published: 14 June 2005

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Cited By

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  • (2023)Discovering Top-k Rules using Subjective and Objective CriteriaProceedings of the ACM on Management of Data10.1145/35889241:1(1-29)Online publication date: 30-May-2023
  • (2023)Scaling Up k-Clique Densest Subgraph DetectionProceedings of the ACM on Management of Data10.1145/35889231:1(1-26)Online publication date: 30-May-2023
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  • (2022)Consistent Answers of Aggregation Queries via SAT2022 IEEE 38th International Conference on Data Engineering (ICDE)10.1109/ICDE53745.2022.00074(924-937)Online publication date: May-2022
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